Prime Intellect
AI Infrastructure
TechnicalAccountManager-AIInfrastructure
Neural analysis suggests this role is
optimal for Mid candidates.
“Technical Account Manager - AI Infrastructure at Prime Intellect. Skills: Customer Ownership, Technical Partnership, Expansion & Renewals, Operational Excellence. Own a portfolio of enterprise customers end-to-end — adoption, retention, expansion, and overall health. Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership”
Industry & Context.
What They're Looking For.
Must Have
3–6 years in Customer Success, Technical Account Management, Solutions Engineering, or adjacent roles at infrastructure, cloud, or AI/ML companies, technical fluency — comfortable reading dashboards, discussing infrastructure architecture, and engaging with customer engineering teams without a translator, commercial instincts — you understand that Customer Success is a revenue function, not a support function, and you can drive real expansion alongside technical outcomes, Deep customer empathy combined with high judgment — you advocate for customers internally while making the calls that are right for the business, Excellent verbal and written communication, especially when explaining complex technical issues to non-technical stakeholders and vice versa, High ownership — you see gaps and build the fix before anyone asks, Comfortable in ambiguity and this market doesn't slow down, AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster
Nice to Have
Direct experience at a cloud provider, AI infrastructure company, or compute marketplace, Familiarity with GPU economics, training and inference workloads, or compute consumption patterns, Background as a TAM or Solutions Architect at a hyperscaler (AWS, GCP, Azure) or specialized cloud provider, Working knowledge of usage-based pricing, capacity commitments, and consumption-based contracts, You've been an early Customer Success hire at a high-growth company
What You'll Do.
Own a portfolio of enterprise customers end-to-end — adoption
Build deep relationships with technical and executive stakeholders at each customer
from ML engineers to engineering leadership
Drive customer outcomes: faster time-to-value on first workloads
smooth scaling as their usage grows
and meaningful expansion as their AI ambitions expand
Understand each customer's training and inference workloads at a real technical level — what models they're training
what infrastructure they need
what their performance bottlenecks are
Partner with customers' engineering teams on cluster performance
workload optimization
Translate customer needs into clear
prioritized feedback for our Engineering and Product teams
Identify expansion opportunities ahead of the customer — anticipate scaling needs
surface new use cases
drive adoption of new products (Lab
additional compute capacity)
Partner with Sales on renewal conversations and growth motions
Maintain visibility into the economics of each customer relationship
in partnership with Finance and Compute
Serve as the first line for customer-facing operational issues — usage questions
incident communications
Build the cross-functional connective tissue between Sales
How You'll Work.
Team & Collaboration
Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership; Partner with customers' engineering teams on cluster performance, capacity planning, workload optimization, and migration; Translate customer needs into clear, prioritized feedback for our Engineering and Product teams; Partner with Sales on renewal conversations and growth motions; Maintain visibility into the economics of each customer relationship, in partnership with Finance and Compute; Build the cross-functional connective tissue between Sales, Engineering, Finance, and customers
Communication Scope
Excellent verbal and written communication, especially when explaining complex technical issues to non-technical stakeholders and vice versa
Full Job Description
TECHNICAL ACCOUNT MANAGER Building Open Superintelligence Infrastructure Prime Intellect is building the open superintelligence stack — from frontier agentic models to the infra that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full RL post-training stack: environments, secure sandboxes, verifiable evals, and our async RL trainer. We enable researchers, startups and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts. We recently raised $15M in funding, led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy, Tri Dao, Dylan Patel, Clem Delangue, Emad Mostaque, and many others. Your Role Prime Intellect serves some of the most sophisticated AI teams in the world that depend on our compute and infrastructure to train and deploy production AI systems. The Customer Success Manager is the person who makes sure those customers succeed, scale, and keep building with us. This is not a traditional Customer Success role. Our customers run large-scale training jobs, scale inference workloads against real production traffic, and depend on cluster reliability and performance the way most companies depend on their cloud provider. The work spans the technical and the commercial — you'll be reading Grafana dashboards and discussing cluster performance with a customer's ML infrastructure team in the morning, and partnering with Sales on a capacity expansion in the afternoon. You'll own a portfolio of enterprise customers end-to-end and build the relationships that make Prime Intellect the partner of choice for their AI infrastructure. Responsibilities Customer Ownership - Own a portfolio of enterprise customers end-to-end — adoption, retention, expansion, and overall health - Build deep relationships with technical and executive stakeholders at each c
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